Stroke survivors partner in research: a case example of collaborative processes
Bibliographic record
Abstract
The Canadian Strategy for Patient-Oriented Research supports the inclusion of patients as partners throughout the research process. Purposeful and meaningful engagement of patient partners after stroke can present unique challenges due to the potential impacts on cognition, communication, or mobility. The purpose of this paper is to provide a case example of working together with three individuals who bring their post-stroke lived experience, including one person with aphasia, from study design through to dissemination. The designed and executed qualitative research was the purpose of this collaboration; this paper describes the collaborative process rather than the outcomes of the original research. The Strategy for Patient-Oriented Research Patient Engagement Framework was followed to engage the patient partners fully as part of the research team. Patient partners were involved at regularly scheduled team meetings and provided guidance on key aspects of project design and decision-making. The patient partners provided robust and important contributions to many aspects of the research, including shaping interview questions, assisting with thematic analysis, and contributing to the dissemination of research findings. Effective team dynamics were fostered by focusing on the value of the lived experience knowledge, using best-practice communication strategies, as well as taking time for relationship-building and story sharing. With appropriate support and guidance, the individuals who have experienced stroke were valuable contributing members of our research team.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.044 | 0.020 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.005 | 0.025 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".